Ying Taur's tools for analysis, with particular focus on microbiome data

yingtools2 is an R package containing many tools and functions for working with clinical and microbiome data.

Install this package from Github:

remotes::install_github("ying14/yingtools2")

Included is a de-identified microbiome dataset of stool samples collected from a cohort of bone marrow transplant recipients at Memorial Sloan Kettering Cancer Center. This was previously published in Clinical Infectious Diseases (2012). The dataset includes sequence data for 439 samples (from 94 patients), as well as a variety of accompanying clinical metadata.

• cid.phy: 16S sequence data (phyloseq object, 1,838,204 seqs, 439 samples, 5,327 OTUs)
• cid.patients: Patients (94 rows)
• cid.hosp: Hospitalizations (314 rows)
• cid.meds: Medications (6,473 rows)
• cid.bsi: Bloodstream Infections (138 rows)
• cid.cdiff: C. diff results (37 rows)

Below are various use coding examples using yingtools2.

For those starting to learn R for data science

• Coding Curriculum. A run-through of the most important R coding skills to learn.
• Regular Expressions. Lists basic regular expression patterns.
• Exercises. These questions test your R skills and range from beginner to advanced.

• Hierarchical clustering (Fig 3A of CID paper)
• PCOA and other ordination methods
• Phylogenetic Trees from Phyloseq
• Testing taxonomic features (LDA effect size)
• Single sample barplot